PI: Dejing Dou

The goals of this project are to (1) evaluate contemporary techniques for deep learning model explanations and (2) utilize DL Explanation approach for improving model performance.

Methods

• Identifying noisy features by aggregating local model approximation via fitting explainable submodels (LIME – local approximation)
• Generating representations of the latent feature space of a model via disentanglement